Cool Car (Wo)Man! – Energy Institute Blog

Peer effects in EV adoption.

The obsession with cool new gadgets, clothes, movies, music and books has kept many conversations going. In the classroom, we’re still teaching an economic model of rational decision-making in a world of perfect information, but the reality of how we learn cool new things has a lot to do with social media. You go to a birthday party and someone tells you about their brand new Tesla! You come to work on a Monday morning and the person in the next cubicle has a new iPhone. Your MBA students tell you that the new Taylor Swift’s Scrapbook fell. The answer is often “I want one too!”

From the perspective of an energy economist, we thought about how to get new, more efficient technologies into people’s hands. Meredith and Duncan were consider heat pumps. Today, I am thinking again of electric vehicles. If we believe the future of transportation is electric, then getting these cool machines into the hands (or under the butts) of people is key. One assumption has been that the ripple effects are important. If Severin gets a Tesla 3 and brings it to work, Max sees it and wants one too, and is more likely to buy a Tesla than that Shelby GT500 he ogled. It makes intuitive sense. But as our readers know, we demand hard, cold numbers.

It is difficult to determine the magnitude of this effect. If I observe the number of Teslas increase more in one neighborhood than another over time, I cannot determine if this is a peer effect or simply that a neighborhood is getting richer (or that something else changes in a different way). What we would like is a natural experience that provides variations in when people choose to buy a car and information on what options are available. Sebastien Tebbea recent visitor to our department, who is in the labor market this year, wrote a really cool paper just do that.

Sebastian uses the fact that some drivers don’t adopt a new car at random times, but rather at 36-month intervals – when their lease expires. And the actual date varies with different drivers. It’s super smart in the first place. But what makes this article blog-worthy is the second part. Sebastian is able to use Swedish household data to determine who is in your family, who lives in your neighborhood, and who is in your work network (people employed by the same company in the same location). “Yeah, Max, but there’s no way he knows what people are driving in these networks.” Sit. Breathe deeply. He. Do. This is an absolutely insane amount of data work. He knows over time which cars enter Max’s family and professional life – which are not his! It then combines this with somewhat random lease renewals to test whether people at lease renewal time who have a higher share of electric and hybrid vehicles in their networks are more likely to buy such a car themselves. Mind blown by empirical genius.

So what do we learn from the paper (yes, these are leases in Sweden, so stick to the hästar external validity):

  1. The article shows (to me) compelling evidence of significant peer effects in EV adoption across all three networks – family, neighborhood, and workplace. What size? One more EV in the neighborhood leads to 0.114 more EVs adopted by neighbors! Hello my neighbors! The corresponding number for workplaces is 0.077 and for families 0.014.
  2. If you do the per capita calculations, the family effect is the most important. So if Aunt Megan buys a Tesla 3, it increases the likelihood that Grandpa won’t get another Volvo V8 but will buy one. The North Star In place.
  3. The effects estimated by Sebastian indicate persistent additional demand. These effects are time-multiplicative, which means that these networks have a strong multiplier effect.
  4. The article suggests that the transition to electric vehicles is strongest away from diesel vehicles, which is great, because diesels are dirty, unpleasant engines from a local and global pollutant perspective.

Of course, research into how to deploy new technologies using social media is not new. There’s some really cool experimental stuff done by people like Kyle Emerick, Betty Sadoulet and Alain de Janvry in the context of new varieties of rice in agriculture. The problem here is the same and the results are not different. Networks are a powerful accelerator for the introduction of new technologies. I will now put my computer down and read more articles on this topic (most of which, unsurprisingly, are written in fields other than economics).

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Suggested citation: Auffhammer, Maximilian. “Cool Car (Wo)Man!” Energy Institute Blog, UC Berkeley, October 24, 2022,

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